The Devil is in the Paperwork:Data Governance Issues
Data solutions for business
Data governance has to become systematic, as big data multiplies in type and volume, and users seek to answer more complex business questions. Data Management has gone from a singular discipline to a more complex discipline, affecting how we conceptualize the problem of Data Management and our understanding of data. Businesses benefit from data governance because it ensures data is consistent and trustworthy. This is critical as more organizations rely on data to make business decisions, optimize operations, create new products and services, and improve profitability.
After years of evolution in
the big data.
Data Governance with hadoop framework Atlas is a scalable and extensible set of core foundational governance services – enabling enterprises to effectively and efficiently meet their compliance requirements within Hadoop and allows integration with the whole enterprise data ecosystem.
Apache Atlas provides open metadata management and governance capabilities for organizations to build a catalog of their data assets, classify and govern these assets and provide collaboration capabilities around these data assets for data scientists, analysts and the data governance team.
Big data technologies enable businesses to quickly collect massive volumes and varieties of data, but because these technologies don’t associate metadata with files, businesses have difficulties determining what data they have. Although this wasn’t a problem historically, as data governance was built into the design of data stores, it now makes data governance difficult at best. Testware Informatics has developed a strategy that addresses this problem in a big data environment. One such method uses application programming interfaces (APIs) that associate metadata with files being brought into a big data platform. In addition to providing metadata, they deliver a level of lineage or traceability and support data security and quality, key components of data governance
How do we measure the quality of our Business ?
“Data Governance will guide the transformation of data and the trusted quality information that supports our decision and actions. Data Governance Framework, We built a maturity model. That model was used to create a set of strategic objectives and a matrix to measure the maturity of the data associated with each of those objectives.
“In our planning sessions, we essentially had two activities. The first was to take all the strategic objectives that we believed would exist in Past years, and then figure out what data is associated with those strategic activities. Then we took each one of those pieces of data and placed it on a maturity matrix where we were measuring how important that data was to that strategic objective and how well-managed we felt the data was today.”
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